Archana Venkataraman

ORCID

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 62

Top Venues

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Naresh Nandakumar, David Hsu, Raheel Ahmed, Archana Venkataraman
A Deep Learning Framework to Localize the Epileptogenic Zone from Dynamic Functional Connectivity Using a Combined Graph Convolutional and Transformer Network. ISBI (2023)
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
A Diffeomorphic Flow-Based Variational Framework for Multi-Speaker Emotion Conversion. IEEE ACM Trans. Audio Speech Lang. Process. 31 (2023)
Saurav Chennuri, Sha Lai, Anne Billot, Maria Varkanitsa, Emily J. Braun, Swathi Kiran, Archana Venkataraman, Janusz Konrad, Prakash Ishwar, Margrit Betke
Fusion Approaches to Predict Post-stroke Aphasia Severity from Multimodal Neuroimaging Data. ICCV (Workshops) (2023)
Niharika Shimona D'Souza, Archana Venkataraman
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. IPMI (2023)
Sarah Wu, Archana Venkataraman, Sayan Ghosal
GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer's Disease Severity. EMBC (2023)
Niharika Shimona D'Souza, Archana Venkataraman
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. CoRR (2023)
Ravi Shankar, Archana Venkataraman
Adaptive Duration Modification of Speech using Masked Convolutional Networks and Open-Loop Time Warping. SSW (2023)
Deeksha M. Shama, Jiasen Jing, Archana Venkataraman
DeepSOZ: A Robust Deep Model for Joint Temporal and Spatial Seizure Onset Localization from Multichannel EEG Data. MICCAI (8) (2023)
Naresh Nandakumar, David Hsu, Raheel Ahmed, Archana Venkataraman
DeepEZ: A Graph Convolutional Network for Automated Epileptogenic Zone Localization From Resting-State fMRI Connectivity. IEEE Trans. Biomed. Eng. 70 (1) (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman
A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease. ICLR (2022)
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
A Diffeomorphic Flow-based Variational Framework for Multi-speaker Emotion Conversion. CoRR (2022)
Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, Haris I. Sair, Archana Venkataraman
RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis. MICCAI (1) (2022)
Jeff Craley, Emily Johnson, Christophe Jouny, David Hsu, Raheel Ahmed, Archana Venkataraman
SZLoc: A Multi-resolution Architecture for Automated Epileptic Seizure Localization from Scalp EEG. MIDL (2022)
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
Prospective Learning: Back to the Future. CoRR (2022)
Ravi Shankar, Abdouh Harouna Kenfack, Arjun Somayazulu, Archana Venkataraman
A Comparative Study of Data Augmentation Techniques for Deep Learning Based Emotion Recognition. CoRR (2022)
Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks. Medical Image Anal. 74 (2021)
Jeff Craley, Emily Johnson, Christophe Jouny, Archana Venkataraman
Automated inter-patient seizure detection using multichannel Convolutional and Recurrent Neural Networks. Biomed. Signal Process. Control. 64 (2021)
Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman
A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space. NeuroImage 238 (2021)
Yu-Chung Peng, Niharika Shimona D'Souza, Brian Bush, Charles Brown, Archana Venkataraman
Predicting Acute Kidney Injury via Interpretable Ensemble Learning and Attention Weighted Convoutional-Recurrent Neural Networks. CISS (2021)
Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart H. Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jennings Zhang, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Anal. 70 (2021)
Ravi Shankar, Archana Venkataraman
A Deep-Bayesian Framework for Adaptive Speech Duration Modification. CoRR (2021)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. CoRR (2021)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. MICCAI (7) (2021)
Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients. IPMI (2021)
Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman
G-MIND: An End-to-End Multimodal Imaging-Genetics Framework for Biomarker Identification and Disease Classification. CoRR (2021)
Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman
G-MIND: an end-to-end multimodal imaging-genetics framework for biomarker identification and disease classification. Medical Imaging: Image Processing (2021)
Danielle Currey, David Hsu, Raheel Ahmed, Archana Venkataraman, Jeff Craley
Cross-site Epileptic Seizure Detection Using Convolutional Neural Networks. CISS (2021)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. MIDL (2021)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. NeuroImage 241 (2021)
Jeff Craley, Emily Johnson, Archana Venkataraman
A Spatio-Temporal Model of Seizure Propagation in Focal Epilepsy. IEEE Trans. Medical Imaging 39 (5) (2020)
Ravi Shankar, Jacob Sager, Archana Venkataraman
Non-parallel Emotion Conversion using a Deep-Generative Hybrid Network and an Adversarial Pair Discriminator. CoRR (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. CoRR (2020)
Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung
Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. CoRR (2020)
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
Multi-speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network. CoRR (2020)
Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. CoRR (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
A joint network optimization framework to predict clinical severity from resting state functional MRI data. NeuroImage 206 (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. CoRR (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. MICCAI (7) (2020)
Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. MLCN/RNO-AI@MICCAI (2020)
Ravi Shankar, Jacob Sager, Archana Venkataraman
Non-Parallel Emotion Conversion Using a Deep-Generative Hybrid Network and an Adversarial Pair Discriminator. INTERSPEECH (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data. CoRR (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart H. Mostofsky, Archana Venkataraman
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations. CoRR (2020)
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
Multi-Speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network. INTERSPEECH (2020)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. CoRR (2020)
Ravi Shankar, Jacob Sager, Archana Venkataraman
A Multi-Speaker Emotion Morphing Model Using Highway Networks and Maximum Likelihood Objective. INTERSPEECH (2019)
Jeff Craley, Emily Johnson, Christophe Jouny, Archana Venkataraman
Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks. MICCAI (4) (2019)
Naresh Nandakumar, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity. CNI@MICCAI (2019)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI (2019)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) (2019)
Jeff Craley, Emily Johnson, Archana Venkataraman
Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG. IPMI (2019)
Ravi Shankar, Archana Venkataraman
Weakly Supervised Syllable Segmentation by Vowel-Consonant Peak Classification. INTERSPEECH (2019)
Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman
A generative-predictive framework to capture altered brain activity in fMRI and its association with genetic risk: application to Schizophrenia. Medical Imaging: Image Processing (2019)
Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman
Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework. MICCAI (4) (2019)
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
Automated Emotion Morphing in Speech Based on Diffeomorphic Curve Registration and Highway Networks. INTERSPEECH (2019)
Jacob Sager, Ravi Shankar, Jacob Reinhold, Archana Venkataraman
VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English. INTERSPEECH (2019)
Naresh Nandakumar, Niharika Shimona D'Souza, Jeff Craley, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman
Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields. CNI@MICCAI (2018)
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) (2018)
Jeff Craley, Emily Johnson, Archana Venkataraman
A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models. MICCAI (3) (2018)
Nicha C. Dvornek, Daniel Y.-J. Yang, Archana Venkataraman, Pamela Ventola, Lawrence H. Staib, Kevin A. Pelphrey, James S. Duncan
Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging. CoRR (2018)
Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel, Stewart Mostofsky
A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. CNI@MICCAI (2017)
Archana Venkataraman, Daniel Y.-J. Yang, Kevin A. Pelphrey, James S. Duncan
Bayesian Community Detection in the Space of Group-Level Functional Differences. IEEE Trans. Medical Imaging 35 (8) (2016)
Andrew Sweet, Archana Venkataraman, Steven M. Stufflebeam, Hesheng Liu, Naoro Tanaka, Joseph R. Madsen, Polina Golland
Detecting Epileptic Regions Based on Global Brain Connectivity Patterns. MICCAI (1) (2013)
Archana Venkataraman, Marek Kubicki, Polina Golland
From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder. IEEE Trans. Medical Imaging 32 (11) (2013)
Archana Venkataraman, Yogesh Rathi, Marek Kubicki, Carl-Fredrik Westin, Polina Golland
Joint Modeling of Anatomical and Functional Connectivity for Population Studies. IEEE Trans. Medical Imaging 31 (2) (2012)
Archana Venkataraman, Marek Kubicki, Polina Golland
From Brain Connectivity Models to Identifying Foci of a Neurological Disorder. MICCAI (1) (2012)
Archana Venkataraman, Marek Kubicki, Carl-Fredrik Westin, Polina Golland
Robust feature selection in resting-state fMRI connectivity based on population studies. CVPR Workshops (2010)
Archana Venkataraman, Yogesh Rathi, Marek Kubicki, Carl-Fredrik Westin, Polina Golland
Joint Generative Model for fMRI/DWI and Its Application to Population Studies. MICCAI (1) (2010)
Archana Venkataraman, Koene R. A. Van Dijk, Randy L. Buckner, Polina Golland
Exploring functional connectivity in fMRI via clustering. ICASSP (2009)
Polina Golland, Danial Lashkari, Archana Venkataraman
Spatial patterns and functional profiles for discovering structure in fMRI data. ACSCC (2008)
Archana Venkataraman, Alan V. Oppenheim
Signal approximation using the bilinear transform. ICASSP (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Archana Venkataraman